Background Ambulance response time is a crucial factor in patient survival. The number of emergen... more Background Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes.
Abstract This paper reports on the smoothing/filtering analysis of a digital surface model (DSM) ... more Abstract This paper reports on the smoothing/filtering analysis of a digital surface model (DSM) derived from LiDAR altimetry for part of the River Coquet, Northumberland, UK using loess regression and the 2D discrete wavelet transform (DWT) implemented in the S-PLUS and R statistical packages.
Background This paper analyses the relationship between public perceptions of access to general p... more Background This paper analyses the relationship between public perceptions of access to general practitioners (GPs) surgeries and hospitals against health status, car ownership and geographic distance. In so doing it explores the different dimensions associated with facility access and accessibility. Methods Data on difficulties experienced in accessing health services, respondent health status and car ownership were collected through an attitudes survey.
Crime has been shown to exhibit marked variations over both space and time. Sherman (1989) report... more Crime has been shown to exhibit marked variations over both space and time. Sherman (1989) reported that 3% of addresses are the subject of 50% of police call for service (Sherman, 1989 p. 3). This is also the case with the temporal dimension; Van Koppen (1999) in his study of commercial robberies reported daily and weekly peaks and distinct increases in winter rather than in summer months.
Abstract This paper describes geographically weighted Poisson regression (GWPR) and its semi-para... more Abstract This paper describes geographically weighted Poisson regression (GWPR) and its semi-parametric variant as a new statistical tool for analysing disease maps arising from spatially non-stationary processes. The method is a type of conditional kernel regression which uses a spatial weighting function to estimate spatial variations in Poisson regression parameters.
ABSTRACT This first working paper from the Environment and Safety Group puts forward a new multi ... more ABSTRACT This first working paper from the Environment and Safety Group puts forward a new multi faceted research agenda arising from the interface between different disciplines. The paper explores the linkages between crime and environment and the assumptions made in the designing out crime debate.
Abstract In this study, we investigate the issue of local collinearity in the predictor data when... more Abstract In this study, we investigate the issue of local collinearity in the predictor data when using geographically weighted regression (GWR) to explore spatial relationships between response and predictor variables. Here we show how the ideas of condition numbers and variance inflation factors may belocalised'to detect and respond to problems caused by this phenomenon.
The aim of this paper is to propose a generalised framework for semiparametric geographically wei... more The aim of this paper is to propose a generalised framework for semiparametric geographically weighted regression (S-GWR) by combining several theoretical aspects of geographically weighted regression (GWR). In this framework, we can implement model selection in order to judge which explanatory effects on the response variable are globally fixed or geographically varying in generalised linear modelling (GLM).
▪ Algorithmically, GWR can be reduced to two functions▪ one to calculate the weights▪ the other t... more ▪ Algorithmically, GWR can be reduced to two functions▪ one to calculate the weights▪ the other to fit the regression▪ d is one of n subsets of the core dataset D. Weights are calculated using function 1 concurrently applied to each of the n subsets. The data, now including weights, are passed to function 2 (a weighted regression fit), concurrently applied to each of the n subsets to give an outcome, z. The results are then pooled for a final assessment.
Abstract The confusion matrix is used to describe land cover accuracy. It describes correspondenc... more Abstract The confusion matrix is used to describe land cover accuracy. It describes correspondence between alternative sources of land cover information and is a standard technique in remote sensing. BUT the confusion matrix is aspatial–it provides no information about the spatial distribution of accuracy. And, despite much work suggesting methods for describing the spatial variation of accuracy (Foody, 2002; 2005), these have not been adopted by the remote sensing community.
Abstract Distance metrics derived from road networks are used in location-allocation models to su... more Abstract Distance metrics derived from road networks are used in location-allocation models to support facility planning. Typically, road networks model 2-dimensional distance (ie over X and Y dimensions). This paper introduces the notion of '3D distance'that incorporates elevation as the Z-dimension in the network.
ABSTRACT Peoples' perception of distance is inaccurate in both real and virtual environments; her... more ABSTRACT Peoples' perception of distance is inaccurate in both real and virtual environments; here, we focus on identifying ways in which these estimations can be improved in Virtual Reality. In this study, overview maps are investigated as an aid to distance estimation, used within the context of a virtual environment for the Sorbas region in SE Spain.
Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequenc... more Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequences of deprivation have different impacts depending upon where a person lives. More geographically minded approaches are alert to spatial variations but are also difficult to compute using desktop PCs.
Site location is an important aspect of spatial planning in public health and decisions about the... more Site location is an important aspect of spatial planning in public health and decisions about the allocation of resources have respond to changing population numbers and distributions. For example, the aged are disproportionately high users of ambulance services (Clark and Fitzgerald, 1999) and are more likely to require ambulances for lifethreatening emergencies (McConnel and Wilson, 1998). In many developed countries the population is predicted to age severely.
Surface-based approaches have frequently been used to analyse social and economic data. Using app... more Surface-based approaches have frequently been used to analyse social and economic data. Using approaches such as kernel regression it has been possible to fit continuous surfaces to spatially reference social and economic data, such as house prices. The technique has often proved a useful tool in identifying trends in the data-for example one can identify areas of town in which housing is generally more costly.
Principal Components Analysis (PCA) is a widely used technique in the social and physical science... more Principal Components Analysis (PCA) is a widely used technique in the social and physical sciences. Originally developed by Pearson (1901), the details of extracting components for a data matrix were presented in an extensive two part paper by Hotelling (1933). In this paper we examine some problems concerning the extraction and interpretation of geographically weighted principal components (Fotheringham et al. 2002: p196-202).
A Digital Elevation Model (DEM) is a representation of geographic reality. The elevations recorde... more A Digital Elevation Model (DEM) is a representation of geographic reality. The elevations recorded within DEMs have been shown to contain errors pertaining to sampling, measurement and interpolation (Fisher, 1998). Even a small amount of elevation error can greatly affect derivative products (Holmes et al., 2000). This can potentially have a significant impact on the application of DEMs in Geographical Information Systems (GIS) where first and second order derivatives are considered.
The error matrix is the most common way of expressing the accuracy of remote sensing image classi... more The error matrix is the most common way of expressing the accuracy of remote sensing image classifications, such as land cover. However, it and the measures that can be calculated from it have been criticised for not providing any indication of the spatial distribution of errors. Other research has identified the need for methods to analyse the spatial non-stationarity of error and to visualise the spatial variation in classification uncertainty.
Abstract In remote sensing the confusion matrix is the most common way of expressing the accuracy... more Abstract In remote sensing the confusion matrix is the most common way of expressing the accuracy of land cover data. Reference land cover data are compared with data for the same locations classified from remotely sensed images in a cross-tabulation. The confusion matrix has been criticised for not containing information relating the spatial distribution of classification errors.
International Journal of Geographical Information Science, Jan 1, 1994
ABSTRACT Simulated vector coastlines of known and varied complexity are rasterized at various lev... more ABSTRACT Simulated vector coastlines of known and varied complexity are rasterized at various levels by the quadtree method. The rasterizing error for each combination of coastline and raster size is calculated by a simple Boolean overlay method. The relationship between line complexity, raster size and rasterizing error is investigated and a method of selecting the most appropriate raster size based on the complexity of the source data and the required level of accuracy is presented.
Background Ambulance response time is a crucial factor in patient survival. The number of emergen... more Background Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes.
Abstract This paper reports on the smoothing/filtering analysis of a digital surface model (DSM) ... more Abstract This paper reports on the smoothing/filtering analysis of a digital surface model (DSM) derived from LiDAR altimetry for part of the River Coquet, Northumberland, UK using loess regression and the 2D discrete wavelet transform (DWT) implemented in the S-PLUS and R statistical packages.
Background This paper analyses the relationship between public perceptions of access to general p... more Background This paper analyses the relationship between public perceptions of access to general practitioners (GPs) surgeries and hospitals against health status, car ownership and geographic distance. In so doing it explores the different dimensions associated with facility access and accessibility. Methods Data on difficulties experienced in accessing health services, respondent health status and car ownership were collected through an attitudes survey.
Crime has been shown to exhibit marked variations over both space and time. Sherman (1989) report... more Crime has been shown to exhibit marked variations over both space and time. Sherman (1989) reported that 3% of addresses are the subject of 50% of police call for service (Sherman, 1989 p. 3). This is also the case with the temporal dimension; Van Koppen (1999) in his study of commercial robberies reported daily and weekly peaks and distinct increases in winter rather than in summer months.
Abstract This paper describes geographically weighted Poisson regression (GWPR) and its semi-para... more Abstract This paper describes geographically weighted Poisson regression (GWPR) and its semi-parametric variant as a new statistical tool for analysing disease maps arising from spatially non-stationary processes. The method is a type of conditional kernel regression which uses a spatial weighting function to estimate spatial variations in Poisson regression parameters.
ABSTRACT This first working paper from the Environment and Safety Group puts forward a new multi ... more ABSTRACT This first working paper from the Environment and Safety Group puts forward a new multi faceted research agenda arising from the interface between different disciplines. The paper explores the linkages between crime and environment and the assumptions made in the designing out crime debate.
Abstract In this study, we investigate the issue of local collinearity in the predictor data when... more Abstract In this study, we investigate the issue of local collinearity in the predictor data when using geographically weighted regression (GWR) to explore spatial relationships between response and predictor variables. Here we show how the ideas of condition numbers and variance inflation factors may belocalised'to detect and respond to problems caused by this phenomenon.
The aim of this paper is to propose a generalised framework for semiparametric geographically wei... more The aim of this paper is to propose a generalised framework for semiparametric geographically weighted regression (S-GWR) by combining several theoretical aspects of geographically weighted regression (GWR). In this framework, we can implement model selection in order to judge which explanatory effects on the response variable are globally fixed or geographically varying in generalised linear modelling (GLM).
▪ Algorithmically, GWR can be reduced to two functions▪ one to calculate the weights▪ the other t... more ▪ Algorithmically, GWR can be reduced to two functions▪ one to calculate the weights▪ the other to fit the regression▪ d is one of n subsets of the core dataset D. Weights are calculated using function 1 concurrently applied to each of the n subsets. The data, now including weights, are passed to function 2 (a weighted regression fit), concurrently applied to each of the n subsets to give an outcome, z. The results are then pooled for a final assessment.
Abstract The confusion matrix is used to describe land cover accuracy. It describes correspondenc... more Abstract The confusion matrix is used to describe land cover accuracy. It describes correspondence between alternative sources of land cover information and is a standard technique in remote sensing. BUT the confusion matrix is aspatial–it provides no information about the spatial distribution of accuracy. And, despite much work suggesting methods for describing the spatial variation of accuracy (Foody, 2002; 2005), these have not been adopted by the remote sensing community.
Abstract Distance metrics derived from road networks are used in location-allocation models to su... more Abstract Distance metrics derived from road networks are used in location-allocation models to support facility planning. Typically, road networks model 2-dimensional distance (ie over X and Y dimensions). This paper introduces the notion of '3D distance'that incorporates elevation as the Z-dimension in the network.
ABSTRACT Peoples' perception of distance is inaccurate in both real and virtual environments; her... more ABSTRACT Peoples' perception of distance is inaccurate in both real and virtual environments; here, we focus on identifying ways in which these estimations can be improved in Virtual Reality. In this study, overview maps are investigated as an aid to distance estimation, used within the context of a virtual environment for the Sorbas region in SE Spain.
Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequenc... more Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequences of deprivation have different impacts depending upon where a person lives. More geographically minded approaches are alert to spatial variations but are also difficult to compute using desktop PCs.
Site location is an important aspect of spatial planning in public health and decisions about the... more Site location is an important aspect of spatial planning in public health and decisions about the allocation of resources have respond to changing population numbers and distributions. For example, the aged are disproportionately high users of ambulance services (Clark and Fitzgerald, 1999) and are more likely to require ambulances for lifethreatening emergencies (McConnel and Wilson, 1998). In many developed countries the population is predicted to age severely.
Surface-based approaches have frequently been used to analyse social and economic data. Using app... more Surface-based approaches have frequently been used to analyse social and economic data. Using approaches such as kernel regression it has been possible to fit continuous surfaces to spatially reference social and economic data, such as house prices. The technique has often proved a useful tool in identifying trends in the data-for example one can identify areas of town in which housing is generally more costly.
Principal Components Analysis (PCA) is a widely used technique in the social and physical science... more Principal Components Analysis (PCA) is a widely used technique in the social and physical sciences. Originally developed by Pearson (1901), the details of extracting components for a data matrix were presented in an extensive two part paper by Hotelling (1933). In this paper we examine some problems concerning the extraction and interpretation of geographically weighted principal components (Fotheringham et al. 2002: p196-202).
A Digital Elevation Model (DEM) is a representation of geographic reality. The elevations recorde... more A Digital Elevation Model (DEM) is a representation of geographic reality. The elevations recorded within DEMs have been shown to contain errors pertaining to sampling, measurement and interpolation (Fisher, 1998). Even a small amount of elevation error can greatly affect derivative products (Holmes et al., 2000). This can potentially have a significant impact on the application of DEMs in Geographical Information Systems (GIS) where first and second order derivatives are considered.
The error matrix is the most common way of expressing the accuracy of remote sensing image classi... more The error matrix is the most common way of expressing the accuracy of remote sensing image classifications, such as land cover. However, it and the measures that can be calculated from it have been criticised for not providing any indication of the spatial distribution of errors. Other research has identified the need for methods to analyse the spatial non-stationarity of error and to visualise the spatial variation in classification uncertainty.
Abstract In remote sensing the confusion matrix is the most common way of expressing the accuracy... more Abstract In remote sensing the confusion matrix is the most common way of expressing the accuracy of land cover data. Reference land cover data are compared with data for the same locations classified from remotely sensed images in a cross-tabulation. The confusion matrix has been criticised for not containing information relating the spatial distribution of classification errors.
International Journal of Geographical Information Science, Jan 1, 1994
ABSTRACT Simulated vector coastlines of known and varied complexity are rasterized at various lev... more ABSTRACT Simulated vector coastlines of known and varied complexity are rasterized at various levels by the quadtree method. The rasterizing error for each combination of coastline and raster size is calculated by a simple Boolean overlay method. The relationship between line complexity, raster size and rasterizing error is investigated and a method of selecting the most appropriate raster size based on the complexity of the source data and the required level of accuracy is presented.
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Papers by Chris Brunsdon